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Current Research and Scholarly Interests

Our goal is to understand the mechanisms regulating the development of human systems (both embryonic and adult). In particular, we are interested in clarifying the roles of both protein coding genes as well as pathobiology (disease state or pathogen) known to be uniquely human ? therefore, not analogously studied in model organisms. Drawing on both pluripotent stem cell biology, hematopoiesis, and immunology, combined with novel high-content single-cell analysis (CyTOF ? Mass Cytometry) and imagining (MIBI-Multiplexed Ion Beam Imaging) we are creating templates of ?normal? human cellular behavior. Using these we can decipher the roles of protein regulators on cellular specification as well as the influence of human-specific pathobiology on system remodeling at the single cell level. This work will enable a better understanding of how disease corrupts this process. Ultimately, our objective will be to use such approaches to not only reveal how novel regulators function in the context of complex cellular systems, but also enable the mechanistic characterization of human pathobiology in primary human tissues. In doing so we will understand how changes in related physiological or pathological systems can be more readily recognized and controlled. In addition to the lab?s work on human hematopoiesis and pluripotent stem cell specification we are seeking collaborative partnerships surrounding problems in human immunology as well as in regenerative medicine, including efforts to exploit next generation single-cell analysis and new computational methods to create systems level models of these processes so that they may be better understood and directed.

Abstract

Acute myeloid leukemia (AML) manifests as phenotypically and functionally diverse cells, often within the same patient. Intratumor phenotypic and functional heterogeneity have been linked primarily by physical sorting experiments, which assume that functionally distinct subpopulations can be prospectively isolated by surface phenotypes. This assumption has proven problematic, and we therefore developed a data-driven approach. Using mass cytometry, we profiled surface and intracellular signaling proteins simultaneously in millions of healthy and leukemic cells. We developed PhenoGraph, which algorithmically defines phenotypes in high-dimensional single-cell data. PhenoGraph revealed that the surface phenotypes of leukemic blasts do not necessarily reflect their intracellular state. Using hematopoietic progenitors, we defined a signaling-based measure of cellular phenotype, which led to isolation of a gene expression signature that was predictive of survival in independent cohorts. This study presents new methods for large-scale analysis of single-cell heterogeneity and demonstrates their utility, yielding insights into AML pathophysiology.

Abstract

Tissue regeneration is an orchestrated progression of cells from an immature state to a mature one, conventionally represented as distinctive cell subsets. A continuum of transitional cell states exists between these discrete stages. We combine the depth of single-cell mass cytometry and an algorithm developed to leverage this continuum by aligning single cells of a given lineage onto a unified trajectory that accurately predicts the developmental path de novo. Applied to human B cell lymphopoiesis, the algorithm (termed Wanderlust) constructed trajectories spanning from hematopoietic stem cells through to naive B cells. This trajectory revealed nascent fractions of B cell progenitors and aligned them with developmentally cued regulatory signaling including IL-7/STAT5 and cellular events such as immunoglobulin rearrangement, highlighting checkpoints across which regulatory signals are rewired paralleling changes in cellular state. This study provides a comprehensive analysis of human B lymphopoiesis, laying a foundation to apply this approach to other tissues and "corrupted" developmental processes including cancer.

Abstract

Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used simultaneously, multiplexed IHC is not routinely used in clinical settings. We have developed a method that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Here, we used MIBI to analyze formalin-fixed, paraffin-embedded human breast tumor tissue sections stained with ten labels simultaneously. The resulting data suggest that MIBI can provide new insights into disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.

Abstract

Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

Abstract

Mutations in the isocitrate dehydrogenase-1 gene (IDH1) are common drivers of acute myeloid leukemia (AML) but their mechanism is not fully understood. It is thought that IDH1 mutants act by inhibiting TET2 to alter DNA methylation, but there are significant unexplained clinical differences between IDH1- and TET2-mutant diseases. We have discovered that mice expressing endogenous mutant IDH1 have reduced numbers of hematopoietic stem cells (HSCs), in contrast to Tet2 knockout (TET2-KO) mice. Mutant IDH1 downregulates the DNA damage (DD) sensor ATM by altering histone methylation, leading to impaired DNA repair, increased sensitivity to DD, and reduced HSC self-renewal, independent of TET2. ATM expression is also decreased in human IDH1-mutated AML. These findings may have implications for treatment of IDH-mutant leukemia.

Abstract

High-throughput single-cell technologies provide an unprecedented view into cellular heterogeneity, yet they pose new challenges in data analysis and interpretation. In this protocol, we describe the use of Spanning-tree Progression Analysis of Density-normalized Events (SPADE), a density-based algorithm for visualizing single-cell data and enabling cellular hierarchy inference among subpopulations of similar cells. It was initially developed for flow and mass cytometry single-cell data. We describe SPADE's implementation and application using an open-source R package that runs on Mac OS X, Linux and Windows systems. A typical SPADE analysis on a 2.27-GHz processor laptop takes ?5 min. We demonstrate the applicability of SPADE to single-cell RNA-seq data. We compare SPADE with recently developed single-cell visualization approaches based on the t-distribution stochastic neighborhood embedding (t-SNE) algorithm. We contrast the implementation and outputs of these methods for normal and malignant hematopoietic cells analyzed by mass cytometry and provide recommendations for appropriate use. Finally, we provide an integrative strategy that combines the strengths of t-SNE and SPADE to infer cellular hierarchy from high-dimensional single-cell data.

Abstract

Recent single-cell analysis technologies offer an unprecedented opportunity to elucidate developmental pathways. Here we present Wishbone, an algorithm for positioning single cells along bifurcating developmental trajectories with high resolution. Wishbone uses multi-dimensional single-cell data, such as mass cytometry or RNA-Seq data, as input and orders cells according to their developmental progression, and it pinpoints bifurcation points by labeling each cell as pre-bifurcation or as one of two post-bifurcation cell fates. Using 30-channel mass cytometry data, we show that Wishbone accurately recovers the known stages of T-cell development in the mouse thymus, including the bifurcation point. We also apply the algorithm to mouse myeloid differentiation and demonstrate its generalization to additional lineages. A comparison of Wishbone to diffusion maps, SCUBA and Monocle shows that it outperforms these methods both in the accuracy of ordering cells and in the correct identification of branch points.

Abstract

The present study describes an efficient and reliable method for the preparation of MS2 viral capsids that are synthetically modified with antibodies using a rapid oxidative coupling strategy. The overall protocol delivers conjugates in high yields and recoveries, requires a minimal excess of antibody to achieve modification of more than 95% of capsids, and can be completed in a short period of time. Antibody-capsid conjugates targeting extracellular receptors on human breast cancer cell lines were prepared and characterized. Notably, conjugation to the capsid did not significantly perturb the binding of the antibodies, as indicated by binding affinities similar to those obtained for the parent antibodies. An array of conjugates was synthesized with various reporters on the interior surface of the capsids to be used in cell studies, including fluorescence-based flow cytometry, confocal microscopy, and mass cytometry. The results of these studies lay the foundation for further exploration of these constructs in the context of clinically relevant applications, including drug delivery and in vivo diagnostics.

Abstract

Immune cells function in an interacting hierarchy that coordinates the activities of various cell types according to genetic and environmental contexts. We developed graphical approaches to construct an extensible immune reference map from mass cytometry data of cells from different organs, incorporating landmark cell populations as flags on the map to compare cells from distinct samples. The maps recapitulated canonical cellular phenotypes and revealed reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune system structure, enabled direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology.

Abstract

Mutant RAS oncoproteins activate signaling molecules that drive oncogenesis in multiple human tumors including acute myelogenous leukemia (AML). However, the specific functions of these pathways in AML are unclear, thwarting the rational application of targeted therapeutics. To elucidate the downstream functions of activated NRAS in AML, we used a murine model that harbors Mll-AF9 and a tetracycline-repressible, activated NRAS (NRAS(G12V)). Using computational approaches to explore our gene-expression data sets, we found that NRAS(G12V) enforced the leukemia self-renewal gene-expression signature and was required to maintain an MLL-AF9- and Myb-dependent leukemia self-renewal gene-expression program. NRAS(G12V) was required for leukemia self-renewal independent of its effects on growth and survival. Analysis of the gene-expression patterns of leukemic subpopulations revealed that the NRAS(G12V)-mediated leukemia self-renewal signature is preferentially expressed in the leukemia stem cell-enriched subpopulation. In a multiplexed analysis of RAS-dependent signaling, Mac-1(Low) cells, which harbor leukemia stem cells, were preferentially sensitive to NRAS(G12V) withdrawal. NRAS(G12V) maintained leukemia self-renewal through mTOR and MEK pathway activation, implicating these pathways as potential targets for cancer stem cell-specific therapies. Together, these experimental results define a RAS oncogene-driven function that is critical for leukemia maintenance and represents a novel mechanism of oncogene addiction.

Abstract

Although pathogens must infect differentiated host cells that exhibit substantial diversity, documenting the consequences of infection against this heterogeneity is challenging. Single-cell mass cytometry permits deep profiling based on combinatorial expression of surface and intracellular proteins. We used this method to investigate varicella-zoster virus (VZV) infection of tonsil Tácells, which mediate viral transport to skin. Our results indicate that VZV induces a continuum of changes regardless of basal phenotypic and functional Tácell characteristics. Contrary to the premise that VZV selectively infects Tácells with skin trafficking profiles, VZV infection altered Tácell surface proteins to enhance or induce these properties. Zap70 and Akt signaling pathways that trigger such surface changes were activated in VZV-infected naive and memory cells by a Tácell receptor (TCR)-independent process. Single-cell mass cytometry is likely to be broadly relevant for demonstrating how intracellular pathogens modulate differentiated cells to support pathogenesis in the natural host.

Abstract

T cell anergy is a key tolerance mechanism to mitigate unwanted T cell activation against self by rendering lymphocytes functionally inactive following Ag encounter. Ag plays an important role in anergy induction where high supraoptimal doses lead to the unresponsive phenotype. How T cells "measure" Ag dose and how this determines functional output to a given antigenic dose remain unclear. Using multiparametric phospho-flow and mass cytometry, we measured the intracellular phosphorylation-dependent signaling events at a single-cell resolution and studied the phosphorylation levels of key proximal human TCR activation- and inhibition-signaling molecules. We show that the intracellular balance and signal integration between these opposing signaling cascades serve as the molecular switch gauging Ag dose. An Ag density of 100 peptide-MHC complexes/cell was found to be the transition point between dominant activation and inhibition cascades, whereas higher Ag doses induced an anergic functional state. Finally, the neutralization of key inhibitory molecules reversed T cell unresponsiveness and enabled maximal T cell functions, even in the presence of very high Ag doses. This mechanism permits T cells to make integrated "measurements" of Ag dose that determine subsequent functional outcomes.

Abstract

New high-dimensional, single-cell technologies offer unprecedented resolution in the analysis of heterogeneous tissues. However, because these technologies can measure dozens of parameters simultaneously in individual cells, data interpretation can be challenging. Here we present viSNE, a tool that allows one to map high-dimensional cytometry data onto two dimensions, yet conserve the high-dimensional structure of the data. viSNE plots individual cells in a visual similar to a scatter plot, while using all pairwise distances in high dimension to determine each cell's location in the plot. We integrated mass cytometry with viSNE to map healthy and cancerous bone marrow samples. Healthy bone marrow automatically maps into a consistent shape, whereas leukemia samples map into malformed shapes that are distinct from healthy bone marrow and from each other. We also use viSNE and mass cytometry to compare leukemia diagnosis and relapse samples, and to identify a rare leukemia population reminiscent of minimal residual disease. viSNE can be applied to any multi-dimensional single-cell technology.

Abstract

The differentiation of ??T cells from thymic precursors is a complex process essential for adaptive immunity. Here we exploited the breadth of expression data sets from the Immunological Genome Project to analyze how the differentiation of thymic precursors gives rise to mature T cell transcriptomes. We found that early T cell commitment was driven by unexpectedly gradual changes. In contrast, transit through the CD4(+)CD8(+) stage involved a global shutdown of housekeeping genes that is rare among cells of the immune system and correlated tightly with expression of the transcription factor c-Myc. Selection driven by major histocompatibility complex (MHC) molecules promoted a large-scale transcriptional reactivation. We identified distinct signatures that marked cells destined for positive selection versus apoptotic deletion. Differences in the expression of unexpectedly few genes accompanied commitment to the CD4(+) or CD8(+) lineage, a similarity that carried through to peripheral T cells and their activation, demonstrated by mass cytometry phosphoproteomics. The transcripts newly identified as encoding candidate mediators of key transitions help define the 'known unknowns' of thymocyte differentiation.

Abstract

Mass cytometry uses atomic mass spectrometry combined with isotopically pure reporter elements to currently measure as many as 40 parameters per single cell. As with any quantitative technology, there is a fundamental need for quality assurance and normalization protocols. In the case of mass cytometry, the signal variation over time due to changes in instrument performance combined with intervals between scheduled maintenance must be accounted for and then normalized. Here, samples were mixed with polystyrene beads embedded with metal lanthanides, allowing monitoring of mass cytometry instrument performance over multiple days of data acquisition. The protocol described here includes simultaneous measurements of beads and cells on the mass cytometer, subsequent extraction of the bead-based signature, and the application of an algorithm enabling correction of both short- and long-term signal fluctuations. The variation in the intensity of the beads that remains after normalization may also be used to determine data quality. Application of the algorithm to a one-month longitudinal analysis of a human peripheral blood sample reduced the range of median signal fluctuation from 4.9-fold to 1.3-fold.

Abstract

Mass cytometry is a recently introduced technology that utilizes transition element isotope-tagged antibodies for protein detection on a single-cell basis. By circumventing the limitations of emission spectral overlap associated with fluorochromes utilized in traditional flow cytometry, mass cytometry currently allows measurement of up to 40 parameters per cell. Recently, a comprehensive mass cytometry analysis was described for the hematopoietic differentiation program in human bone marrow from a healthy donor. The current study describes approaches to delineate cell cycle stages utilizing 5-iodo-2-deoxyuridine (IdU) to mark cells in S phase, simultaneously with antibodies against cyclin B1, cyclin A, and phosphorylated histone H3 (S28) that characterize the other cell cycle phases. Protocols were developed in which an antibody against phosphorylated retinoblastoma protein (Rb) at serines 807 and 811 was used to separate cells in G0 and G1 phases of the cell cycle. This mass cytometry method yielded cell cycle distributions of both normal and cancer cell populations that were equivalent to those obtained by traditional fluorescence cytometry techniques. We applied this to map the cell cycle phases of cells spanning the hematopoietic hierarchy in healthy human bone marrow as a prelude to later studies with cancers and other disorders of this lineage.

Abstract

In recent years, major advances in single-cell measurement systems have included the introduction of high-throughput versions of traditional flow cytometry that are now capable of measuring intracellular network activity, the emergence of isotope labels that can enable the tracking of a greater variety of cell markers and the development of super-resolution microscopy techniques that allow measurement of RNA expression in single living cells. These technologies will facilitate our capacity to catalog and bring order to the inherent diversity present in cancer cell populations. Alongside these developments, new computational approaches that mine deep data sets are facilitating the visualization of the shape of the data and enabling the extraction of meaningful outputs. These applications have the potential to reveal new insights into cancer biology at the intersections of stem cell function, tumor-initiating cells and multilineage tumor development. In the clinic, they may also prove important not only in the development of new diagnostic modalities but also in understanding how the emergence of tumor cell clones harboring different sets of mutations predispose patients to relapse or disease progression.

Abstract

In recent years, advances in technology have provided us with tools to quantify the expression of multiple genes in individual cells. The ability to measure simultaneously multiple genes in the same cell is necessary to resolve the great diversity of cell subsets, as well as to define their function in the host. Fluorescence-based flow cytometry is the benchmark for this; with it, we can quantify 18 proteins per cell, at >10 000 cells/s. Mass cytometry is a new technology that promises to extend these capabilities significantly. Immunophenotyping by mass spectrometry provides the ability to measure >36 proteins at a rate of 1000 cells/s. We review these cytometric technologies, capable of high-content, high-throughput single-cell assays.

Abstract

Cytotoxic CD8(+) T lymphocytes directly kill infected or aberrant cells and secrete proinflammatory cytokines. By using metal-labeled probes and mass spectrometric analysis (cytometry by time-of-flight, or CyTOF) of human CD8(+) T cells, we analyzed the expression of many more proteins than previously possible with fluorescent labels, including surface markers, cytokines, and antigen specificity with modified peptide-MHC tetramers. With 3-dimensional principal component analysis (3D-PCA) to display phenotypic diversity, we observed a relatively uniform pattern of variation in all subjects tested, highlighting the interrelatedness of previously described subsets and the continuous nature of CD8(+) T cell differentiation. These data also showed much greater complexity in the CD8(+) T cell compartment than previously appreciated, including a nearly combinatorial pattern of cytokine expression, with distinct niches occupied by virus-specific cells. This large degree of functional diversity even between cells with the same specificity gives CD8(+) T cells a remarkable degree of flexibility in responding to pathogens.

Abstract

The ability to analyze multiple single-cell parameters is critical for understanding cellular heterogeneity. Despite recent advances in measurement technology, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system. To objectively uncover cellular heterogeneity from single-cell measurements, we present a versatile computational approach, spanning-tree progression analysis of density-normalized events (SPADE). We applied SPADE to flow cytometry data of mouse bone marrow and to mass cytometry data of human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. We demonstrate that SPADE is robust to measurement noise and to the choice of cellular markers. SPADE facilitates the analysis of cellular heterogeneity, the identification of cell types and comparison of functional markers in response to perturbations.

Abstract

Human embryonic stem cells (hESCs) have unique self-renewal and differentiation properties, which are experimentally measured using functional assays. hESC cultures are known to be heterogeneous, but whether subsets of cells contribute differently to functional assays has yet to be examined. Here, using clonal tracking by retroviral integration, we analyzed in situ the propensity of individual hESCs to contribute to different functional assays. We observed different clonal distributions in teratomas versus in vitro differentiation assays. Some hESC subsets apparently contributed substantially to lineage-specific embryoid body differentiation and lacked clonogenic capacity, although they had self-renewal ability. In contrast, other subsets of self-renewing hESCs with clonogenic ability contributed to teratoma formation but were less frequently observed after in vitro differentiation. Our study suggests that assays used to measure pluripotency may detect distinct subsets of hESCs. These findings have direct implications for hESC-based therapies that may be optimized based on such functional assays.

Abstract

We performed a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in liquid chromatography-mass spectrometry-based proteomics. We distributed an equimolar test sample, comprising 20 highly purified recombinant human proteins, to 27 laboratories. Each protein contained one or more unique tryptic peptides of 1,250 Da to test for ion selection and sampling in the mass spectrometer. Of the 27 labs, members of only 7 labs initially reported all 20 proteins correctly, and members of only 1 lab reported all tryptic peptides of 1,250 Da. Centralized analysis of the raw data, however, revealed that all 20 proteins and most of the 1,250 Da peptides had been detected in all 27 labs. Our centralized analysis determined missed identifications (false negatives), environmental contamination, database matching and curation of protein identifications as sources of problems. Improved search engines and databases are needed for mass spectrometry-based proteomics.

Abstract

The derivation and long-term maintenance of human embryonic stem cells (hESCs) has been established in culture formats that are both dependent and independent of support (feeder) cells. However, the factors responsible for preserving the viability of hESCs in a nascent state remain unknown. We describe a mass spectrometry-based method for probing the secretome of the hESC culture microenvironment to identify potential regulating protein factors that are in low abundance. Individual samples were analyzed several times, using successive mass (m/z) and retention time-directed exclusion, without sampling the same peptide ion twice. This iterative exclusion -mass spectrometry (IE-MS) approach more than doubled protein and peptide metrics in comparison to a simple repeat analysis method on the same instrument, even after extensive sample pre-fractionation. Furthermore, implementation of the IE-MS approach was shown to enhance the performance of an older quadrupole time of flight (Q-ToF) MS. The resulting number of identified peptides approached that of a parallel repeat analysis on a newer LTQ-Orbitrap MS. The combination of the results of both instruments proved to be superior to that achieved by a single instrument in the identification of additional proteins. Using the IE-MS strategy, combined with complementary gel- and solution-based fractionation methods, the hESC culture microenvironment was extensively probed. Over 10 to 12 times more extracellular proteins were observed compared with previously published surveys. The detection of previously undetectable growth factors, present at concentrations ranging from 10(-9) to 10(-11) g/ml, highlights the depth of our profiling. The IE-MS approach provides a simple and reliable technique that greatly enhances instrument performance by increasing the effective depth of MS-based proteomic profiling. This approach should be widely applicable to any LC-MS/MS instrument platform or biological system.

Abstract

Recent studies using stable isotope labeling with amino acids in culture (SILAC) in quantitative proteomics have made mention of the problematic conversion of isotope-coded arginine to proline in cells. The resulting converted proline peptide divides the heavy peptide ion signal causing inaccuracy when compared with the light peptide ion signal. This is of particular concern as it can effect up to half of all peptides in a proteomic experiment. Strategies to both compensate for and limit the inadvertent conversion have been demonstrated, but none have been shown to prevent it. Additionally, these methods combined with SILAC labeling in general have proven problematic in their large scale application to sensitive cell types including embryonic stem cells (ESCs) from the mouse and human. Here, we show that by providing as little as 200 mg/liter L-proline in SILAC media, the conversion of arginine to proline can be rendered completely undetectable. At the same time, there was no compromise in labeling with isotope-coded arginine, indicating there is no observable back conversion from the proline supplement. As a result, when supplemented with proline, correct interpretation of "light" and "heavy" peptide ratios could be achieved even in the worst cases of conversion. By extending these principles to ESC culture protocols and reagents we were able to routinely SILAC label both mouse and human ESCs in the absence of feeder cells and without compromising the pluripotent phenotype. This study provides the simplest protocol to prevent proline artifacts in SILAC labeling experiments with arginine. Moreover, it presents a robust, feeder cell-free, protocol for performing SILAC experiments on ESCs from both the mouse and the human.

Abstract

The factors and signaling pathways controlling pluripotent human cell properties, both embryonic and induced, have not been fully investigated. Failure to account for functional heterogeneity within human embryonic stem cell (hESC) cultures has led to inconclusive results in previous work examining extrinsic influences governing hESC fate (self renewal vs. differentiation vs. death). Here, we attempt to reconcile these inconsistencies with recent reports demonstrating that an autologously produced in vitro niche regulates hESCs. Moreover, we focus on the reciprocal paracrine signals within the in vitro hESC niche allowing for the maintenance and/or expansion of the hESC colony-initiating cell (CIC). Based on this, it is clear that separation of hESC-CICs, apart from their differentiated derivatives, will be essential in future studies involving their molecular regulation. Understanding how extrinsic factors control hESC self-renewal and differentiation will allow us to culture and differentiate these pluripotent cells with higher efficiency. This knowledge will be essential for clinical applications using human pluripotent cells in regenerative medicine.

Abstract

In vivo the stem cell niche is an essential component in controlling and maintaining the stem cells' ability to survive and respond to injury. Human embryonic stem cells (hESCs) appear to be an exception to this rule as they can be removed from their blastocytic microenvironment and maintained indefinitely in vitro. However, recent observations reveal the existence of an autonomously derived in vitro hESC niche. This provides a previously unappreciated mechanism to control hESC expansion and differentiation. Recognizing this, it may now be possible to take aspects of in vivo stem cell niches, namely extracellular matrices, paracrine signals and accessory cell types, and exploit them in order to gain fidelity in directed hESC differentiation. In doing so, routine customization of hESC lines and their application in regenerative therapies may be further enhanced using unique hESC niche-based approaches.

Abstract

Mass spectrometry (MS)-based proteomics has become one of the most powerful tools for identifying expressed proteins, providing quick insights into molecular and cellular biology. Traditionally, proteins isolated by either one- or two-dimensional gel electrophoresis are digested with a site specific protease. The resulting peptides are subject to one of two forms of analysis: (1) matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, where a "mass fingerprint" of all the peptides in a sample is generated, or (2) electrospray ionization tandem MS (ESI-MS/MS), where a mass fragmentation spectra is generated for each peptide in a sample. The resulting mass information is then compared to that of a theoretical database created with available genomic sequence information. This unit provides protocols for this type of assessment in embryonic stem cells (ESCs).

Abstract

Human embryonic stem cell (hESC) lines are known to be morphologically and phenotypically heterogeneous. The functional nature and relationship of cells residing within hESC cultures, however, has not been evaluated because isolation of single hESCs is limited to drug or manual selection. Here we provide a quantitative method using flow cytometry to isolate and clonally expand hESCs based on undifferentiated markers, alone or in combination with a fluorescent reporter. This method allowed for isolation of stage-specific embryonic antigen-3-positive (SSEA-3+) and SSEA-3- cells from hESC cultures. Although both SSEA-3+ and SSEA-3- cells could initiate pluripotent hESC cultures, we show that they possess distinct cell-cycle properties, clonogenic capacity and expression of ESC transcription factors. Our study provides formal evidence for heterogeneity among self-renewing pluripotent hESCs, illustrating that this isolation technique will be instrumental in further dissecting the biology of hESC lines.